The face detection node finds faces in images and video frames and, optionally, computes face embeddings (vectors) that can be used for recognition and clustering. Video is processed by scanning frames at a configurable rate.
Kind |
|
Applies to |
Image, Video |
Inputs |
None |
Output keys |
|
Requirements |
InspireFace native runtime and its model pack. CPU works; a GPU-enabled pack accelerates video/large batches. Model files require local storage and memory. |
Persists to |
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Configuration
FacedetectNodeOptions:
| Option | Meaning |
|---|---|
|
Path to the InspireFace model pack |
|
Which InspireFace capabilities to enable (detection, recognition, …) |
|
How often to sample frames from a video |
|
Frame scale used before detection |
|
Minimum face size (as a fraction of frame height) to keep |
|
Clustering parameters for grouping embeddings into persons |
Use Cases
-
Face search & recognition — match a query face against embeddings across the library.
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Person clustering — group appearances of the same person via the embedding clusters.
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Content moderation / review — flag assets that contain people.
-
Feed Face Description with detected faces.